509 research outputs found
Simple QED- and QCD-like Models at Finite Density
In this paper we discuss one-dimensional models reproducing some features of
quantum electrodynamics and quantum chromodynamics at nonzero density and
temperature. Since a severe sign problem makes a numerical treatment of QED and
QCD at high density difficult, such models help to explore various effects
peculiar to the full theory. Studying them gives insights into the large
density behavior of the Polyakov loop by taking both bosonic and fermionic
degrees of freedom into account, although in one dimension only the
implementation of a global gauge symmetry is possible. For these models we
evaluate the respective partition functions and discuss several observables as
well as the Silver Blaze phenomenon.Comment: 5 pages, 2 figures. Final published versio
Asymptotics of large eigenvalues for a class of band matrices
We investigate the asymptotic behaviour of large eigenvalues for a class of
finite difference self-adjoint operators with compact resolvent in
Metatranscriptome Profiling Indicates Size-Dependent Differentiation in Plastic and Conserved Community Traits and Functional Diversification in Dinoflagellate Communities
Communities of microscopic dinoflagellates are omnipresent in aquatic ecosystems. Consequently, their traits drive community processes with profound effects on global biogeochemistry. Species traits are, however, not necessarily static but respond to environmental changes in order to maintain fitness and may differ with cell size that scales physiological rates. Comprehending such trait characteristics is necessary for a mechanistic understanding of plankton community dynamics and resulting biogeochemical impacts. Here, we used information theory to analyze metatranscriptomes of micro- and nano-dinoflagellate communities in three ecosystems. Measures of gene expression variations were set as a proxy to determine conserved and plastic community traits and the environmental influence on trait changes. Using metabarcoding, we further investigated if communities with a more similar taxon composition also express more similar traits. Our results indicate that plastic community traits mainly arise from membrane vesicle associated processes in all the environments we investigated. A specific environmental influence on trait plasticity was observed to arise from nitrogen availability in both size classes. Species interactions also appeared to be responsible for trait plasticity in the smaller-sized dinoflagellates. Additionally, the smaller-sized dinoflagellate communities are characterized by the expression of a large pool of habitat specific genes despite being taxonomically more similar across the habitats, in contrast to the microplanktonic assemblages that adapted to their environments by changing species composition. Our data highlight the functional diversification on the gene level as a signature of smaller sized dinoflagellates, nitrogen availability and species interactions as drivers of trait plasticity, and traits most likely linked to fitness and community performance
Central coordination as an alternative for local coordination in a multicenter randomized controlled trial: the FAITH trial experience
Contains fulltext :
110505.pdf (publisher's version ) (Open Access)BACKGROUND: Surgeons in the Netherlands, Canada and the US participate in the FAITH trial (Fixation using Alternative Implants for the Treatment of Hip fractures). Dutch sites are managed and visited by a financed central trial coordinator, whereas most Canadian and US sites have local study coordinators and receive per patient payment. This study was aimed to assess how these different trial management strategies affected trial performance. METHODS: Details related to obtaining ethics approval, time to trial start-up, inclusion, and percentage completed follow-ups were collected for each trial site and compared. Pre-trial screening data were compared with actual inclusion rates. RESULTS: Median trial start-up ranged from 41 days (P25-P75 10-139) in the Netherlands to 232 days (P25-P75 98-423) in Canada (p = 0.027). The inclusion rate was highest in the Netherlands; median 1.03 patients (P25-P75 0.43-2.21) per site per month, representing 34.4% of the total eligible population. It was lowest in Canada; 0.14 inclusions (P25-P75 0.00-0.28), representing 3.9% of eligible patients (p < 0.001). The percentage completed follow-ups was 83% for Canadian and Dutch sites and 70% for US sites (p = 0.217). CONCLUSIONS: In this trial, a central financed trial coordinator to manage all trial related tasks in participating sites resulted in better trial progression and a similar follow-up. It is therefore a suitable alternative for appointing these tasks to local research assistants. The central coordinator approach can enable smaller regional hospitals to participate in multicenter randomized controlled trials. Circumstances such as available budget, sample size, and geographical area should however be taken into account when choosing a management strategy. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00761813
Linking Symptom Inventories using Semantic Textual Similarity
An extensive library of symptom inventories has been developed over time to
measure clinical symptoms, but this variety has led to several long standing
issues. Most notably, results drawn from different settings and studies are not
comparable, which limits reproducibility. Here, we present an artificial
intelligence (AI) approach using semantic textual similarity (STS) to link
symptoms and scores across previously incongruous symptom inventories. We
tested the ability of four pre-trained STS models to screen thousands of
symptom description pairs for related content - a challenging task typically
requiring expert panels. Models were tasked to predict symptom severity across
four different inventories for 6,607 participants drawn from 16 international
data sources. The STS approach achieved 74.8% accuracy across five tasks,
outperforming other models tested. This work suggests that incorporating
contextual, semantic information can assist expert decision-making processes,
yielding gains for both general and disease-specific clinical assessment
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